4.7 Article

An exact algorithm for scheduling tandem quay crane operations in container terminals

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2022.102949

关键词

Container terminal; Tandem quay crane; Integer programming; Logic-based benders decomposition algorithm

资金

  1. National Nature Science Foundation of China
  2. Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University, China
  3. [71971035]
  4. [71572022]

向作者/读者索取更多资源

This study investigates the scheduling problem of tandem quay crane at container terminals and proposes a novel integer linear programming model to minimize unloading time. By introducing valid inequalities and logic-based Benders decomposition algorithm, the convergence speed of the algorithm can be accelerated, and computational results show that the proposed model is superior to previous models.
This study investigates the scheduling problem of the tandem quay crane (TQC), which is a new type of loading/unloading device used at container terminals. The TQC can execute either a single-lift or tandem-lift at a time. Considering the changeover time between the above two operational modes of the TQC and the weight limitation for executing a tandem-lift, a novel integer linear programming model is established to minimize the time needed for unloading the containers from the containership, and valid inequalities are introduced to enhance the model. Then, an exact algorithm based on logic-based Benders decomposition is applied to solve the problem. The proposed approach decomposes the problem into a mode-assignment master problem and an operation-sequencing slave problem. Logic-based cuts are proposed to ensure the convergence of the algorithm, and several enhancement measures are developed to accelerate the convergence speed. The computational results indicate that the model is superior to the previous model proposed in the literature, and the proposed inequalities are effective. Moreover, the exact algorithm was verified to be efficient for solving realistically sized instances within an acceptable time.

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